Modeling Rainfall Conditions For Shallow Landsliding In Seattle, Washington
We describe the results from an application of a distributed, transient infiltration–slope-stability model for an 18 km 2 area of southwestern Seattle, Washington, USA. The model (TRIGRS) combines an infinite slope-stability calculation and an analytic, one-dimensional solution for pore-pressure dif...
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Veröffentlicht in: | Reviews in engineering geology 2008-01, Vol.20, p.137 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | We describe the results from an application of a distributed, transient infiltration–slope-stability model for an 18 km 2 area of southwestern Seattle, Washington, USA. The model (TRIGRS) combines an infinite slope-stability calculation and an
analytic, one-dimensional solution for pore-pressure diffusion in a soil layer of finite depth in response to time-varying
rainfall. The transient solution for pore-pressure response can be superposed on any steady-state groundwater-flow field that
is consistent with model assumptions. Applied over digital topography, the model computes a factor of safety for each grid
cell at any time during a rainstorm. Input variables may vary from cell to cell, and the rainfall rate can vary in both space
and time. For Seattle, topographic slope derived from an airborne laser swath mapping (ALSM)–based 3 m digital elevation model
(DEM), maps of soil and water-table depths derived from geotechnical borings, and hourly rainfall intensities were used as
model inputs. Material strength and hydraulic properties used in the model were determined from field and laboratory measurements,
and a tension-saturated initial condition was assumed. Results are given in terms of a destabilizing intensity and duration
of rainfall, and they were evaluated by comparing the locations of 212 historical landslides with the area mapped as potentially
unstable. Because the equations of groundwater flow are explicitly solved with respect to time, the results from TRIGRS simulations
can be portrayed quantitatively to assess the potential landslide hazard based on rainfall conditions. |
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ISSN: | 0080-2018 2169-799X |
DOI: | 10.1130/2008.4020(08) |